Update app.py

app.py

@@ -1,53 +1,47 @@
-@app.function(
+import gradio as gr
+
 class InteractiveChat:
-    def __init__(self, model_name="openai/whisper-large", tts_choice="OpenVoice", **kwargs):
-        self.whisper_processor = WhisperProcessor.from_pretrained(model_name)
-        self.whisper_model = WhisperForConditionalGeneration.from_pretrained(model_name)
+
+    whisper_processor = WhisperProcessor.from_pretrained("openai/whisper-large") 
+    whisper_model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large")
+
+    def __init__(self):
         self.zephyr_tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
         self.zephyr_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta", device_map="auto")
-        self.zephyr_pipeline = pipeline("text-generation", model=self.zephyr_model, tokenizer=self.zephyr_tokenizer)
-        self.tts_choice = tts_choice
 
     def generate_response(self, input_data):
-        input_features = self.whisper_processor(input_data, sampling_rate=16_000, return_tensors="pt").input_features
+        input_features = self.whisper_processor(input_data)  
         predicted_ids = self.whisper_model.generate(input_features)
-        transcription = self.whisper_processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
-
+        transcription = self.whisper_processor.batch_decode(predicted_ids)
+        
+        response = self.get_zephyr_response(transcription)
+        
+        self.speak(response)
+        return response
 
-        response = self.zephyr_pipeline(transcription, max_length=1000)[0]["generated_text"]
-        return transcription, response
+    def get_zephyr_response(self, transcription):
+        zephyr_pipeline = pipeline("text-generation")  
+        response = zephyr_pipeline(transcription)[0]["generated_text"]
+        return response
 
     def speak(self, text):
-        try:
-            if self.tts_choice == "OpenVoice":
-                model_path = snapshot_download("facebook/mms-tts-eng")
-                pipe = pipeline("text-to-speech", model=model_path)
-                audio_array = pipe(text).audio
-                pygame.mixer.init()
-                sound = pygame.sndarray.make_sound(audio_array)
-                sound.play()
-                pygame.time.delay(int(sound.get_length() * 1000))
-            else:  # gTTS
-                tts = gTTS(text=text, lang='en')
-                tts.save("response.mp3")
-                pygame.mixer.init()
-                pygame.mixer.music.load("response.mp3")
-                pygame.mixer.music.play()
-                while pygame.mixer.music.get_busy():
-                    pygame.time.Clock().tick(10)
-        except Exception as e:
-            print("Error occurred during speech generation:", e)
-
-
-with gr.Blocks() as demo:
-    model_choice = gr.Dropdown(["openai/whisper-large"], label="Whisper Model", value="openai/whisper-large")
-    tts_choice = gr.Radio(["OpenVoice", "gTTS"], label="TTS Engine", value="OpenVoice")
-    input_data = gr.Audio(source="microphone", type="numpy", label="Speak Your Message")
-    output_text = gr.Textbox(label="Transcription and Response")
-
-    model_choice.change(lambda x, y: InteractiveChat(x, y), inputs=[model_choice, tts_choice], outputs=None)
-    tts_choice.change(lambda x, y: InteractiveChat(y, x), inputs=[tts_choice, model_choice], outputs=None)
-    input_data.change(lambda x, model: model.generate_response(x), inputs=[input_data, model_choice],
-                      outputs=output_text)
-    input_data.change(lambda x, model: model.speak(x[1]), inputs=[output_text, model_choice],
-                      outputs=None))  # Speak the response
+        speech_client = SpeechClient() 
+        speech_client.synthesize(text)
+
+    def generate_response(self, input):
+      
+        # get transcription from Whisper
+      
+        response = self.get_zephyr_response(transcription)
+        
+        self.speak(response)
+        
+        return response
+
+interface = gr.Interface(
+  gr.Audio(type="microphone"), 
+  gr.Textbox(),
+  self.generate_response
+)
+
+interface.launch()